Referencing Anthropic’s recent blog post on “Code execution with MCP: building more efficient AI agents,” (Code execution with MCP: building more efficient AI agents \ Anthropic)
how can we use or replicate this code execution flow in Cursor AI? Specifically, I’m interested in:
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What steps are required to set up Cursor AI to execute code in an MCP-style environment (where the agent writes and runs code to access tools dynamically, rather than loading all tool parameters up front)?
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Are there guides or examples for configuring MPC servers or workflows in Cursor to handle large data sets efficiently and securely as described in the blog (including in-context data filtering and privacy masking)?
Any pointers, documentation links, or community examples would be highly appreciated!